Improving Transformer-based Sequential Conversational Recommendations through Knowledge Graph Embeddings-Reference-Cited by-同舟云学术

Improving Transformer-based Sequential Conversational Recommendations through Knowledge Graph Embeddings

Published:2024-06-22 Issue: Volume:30 Page:172-182
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Container-title:Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization
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Author:

Petruzzelli Alessandro¹^ORCID,Martina Alessandro Francesco Maria²^ORCID,Spillo Giuseppe³^ORCID,Musto Cataldo⁴^ORCID,De Gemmis Marco⁵^ORCID,Lops Pasquale⁶^ORCID,Semeraro Giovanni⁷^ORCID

Affiliation:

1. Department of Computer Science, University of Bari Aldo moro, Italy

2. University of Bari Aldo Moro, Italy

3. Computer Science, University of Bari, Italy

4. Department of Computer Science, Dipartimento di Informatica - University of Bari, Italy

5. Dept. of Computer Science, University of Bari Aldo Moro, Dept. of Computer Science, Italy

6. Department of Computer Science, University of Bari, Italy

7. University of Bari, Italy

Funder

PNRR project FAIR - Future AI Research (PE00000013), Spoke 6 - Symbiotic AI

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3627043.3659565

Reference51 articles.

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2. Giacomo Balloccu, Ludovico Boratto, Gianni Fenu, Francesca Maridina Malloci, and Mirko Marras. 2024. Explainable Recommender Systems with Knowledge Graphs and Language Models. In European Conference on Information Retrieval. Springer, 352–357.

3. Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations

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